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What is the Negative Volume Index?

What is the Negative Volume Index?

Understanding various technical indicators is crucial for making informed investment decisions. One such indicator is the Negative Volume Index (NVI). By tracking decreases in trading volume and their associated price changes, NVI offers unique insights into market behavior and investor sentiment. This article delves into the concept, functionality, and application of the Negative Volume Index.

Negative Volume Index: The Basics

The Negative Volume Index is a technical indicator developed by Paul Dysart to track the decline in trading volumes and the corresponding price changes of securities or indexes. The indicator's design focuses on days when trading volume is less than the previous day, highlighting the actions of institutional investors and fund managers in quieter market conditions.

In essence, the NVI interprets market dynamics by considering how lower trading volumes impact price movements. If the market continues to perform well amidst decreasing trading volumes, it suggests a robust bullish primary trend not manipulated by artificial trading volumes.

Historical Perspective and Renewed Interest

Originally applied to market indexes, the NVI gained renewed interest when Norman Fosback refined it in his book "Stock Market Logic" in the 1970s. Dysart viewed the NVI's behavior as a potent indicator of bull market conditions, a belief that has largely been validated by subsequent analyses, despite some initial skepticism in the 1960s.

Fosback argued that the uninformed majority of investors tend to be most active on high-volume days. Therefore, tracking the NVI could yield valuable insights about the "smart money" or informed investors' actions on low-volume days.

Utilizing the NVI for Trend Analysis

A key part of using the NVI involves looking at the 200- or 250-day moving average as a crossover point. When the NVI crosses this average, it often signals a change in the primary trend, whether bullish or bearish.

The NVI, used in conjunction with the Positive Volume Index (PVI), provides better context for understanding market behavior. While both NVI and PVI can be effective standalone indicators, they are not infallible. Whipsaws—erratic fluctuations that can trigger market orders—can obscure true trends, and other irregularities might occur.

The Role of AI in Enhancing NVI Analysis

To navigate these potential challenges, savvy traders often look for additional signals to validate or question potential trading decisions. Artificial Intelligence tools, such as Tickeron’s A.I.dvisor, provide powerful ways to evaluate trade ideas, analyze signals, and provide the necessary confirmation for rational, emotionless, and effective trading decisions.

The NVI: A Tool to Track Institutional Investors

The NVI offers a graphical representation of how price movements are affected by down volume days, integrating both volume and price. By following NVI trendlines, investors can potentially track mainstream, smart money movements typically associated with institutional investors. This strategy allows for understanding how price is influenced by volume, a critical aspect of trading dynamics.

The Negative Volume Index is a powerful tool in an investor's arsenal, providing vital insights into market dynamics on low-volume days. Despite its inherent limitations, with careful analysis and the support of complementary indicators or AI-based tools, the NVI can contribute to more informed and potentially profitable trading decisions.


The Negative Volume Index (NVI) is a technical indicator that tracks decreases in trade volume for an index or security, as well as price changes on those days. Paul Dysart developed the original version of this indicator for market indexes, and it garnered renewed attention when it was reworked in the 1970s via Norman Fosback in his book Stock Market Logic.

The price changes in a security or the percentage change in an index are only added to or subtracted from the Negative Volume Index on days when the trading volume is lower than the day before. By watching market movement on days with lower trading volume, investors can identify where institutions and fund managers are moving their money. If trading volume is down and the market continues to do well, it means that there is a strong bullish primary trend, and that trading volume is not artificially pushing prices around.

This particular phenomenon was what Dysart considered the strongest indicator of bull market conditions. It has held up in most analysis, even though he was troubled by its lack of viability in the 1960s. Fosback noted that the uninformed majority of investors were likely to be active on the days when the volume was highest, and both analysts felt that paying close attention the Negative Volume Index would better indicate what the smart money was doing.

The 200- or 250-day moving average of the NVI is used as the crossover point, after which a primary trend change (bullish or bearish) is thought to be indicated.

The NVI and PVI can be used together to give better context to the market, but while both indicators can be effective on their own and together, no indicator is 100% accurate. Whipsaws can obscure true trends, and other irregularities may arise. That’s why savvy traders will look for additional signals to confirm – or force them to reconsider – potential trading decisions. Tickeron’s Artificial Intelligence, known as A.I.dvisor, gives traders powerful ways to evaluate trade ideas, analyze signals, and provide the key confirmation needed to make rational, emotionless, and effective trades.

Tickeron's Offerings

The fundamental premise of technical analysis lies in identifying recurring price patterns and trends, which can then be used to forecast the course of upcoming market trends. Our journey commenced with the development of AI-based Engines, such as the Pattern Search Engine, Real-Time Patterns, and the Trend Prediction Engine, which empower us to conduct a comprehensive analysis of market trends. We have delved into nearly all established methodologies, including price patterns, trend indicators, oscillators, and many more, by leveraging neural networks and deep historical backtests. As a consequence, we've been able to accumulate a suite of trading algorithms that collaboratively allow our AI Robots to effectively pinpoint pivotal moments of shifts in market trends.

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